There has always been a need in society for verifying a person's identity for a variety of purposes. Modern day scientific technology has adopted the widespread use of computers and related mechanisms for the purposes of giving credit, performing electronic funds transfer, and so forth. In all facets of the financial community including the retail industry, securities industry, banking and the like, sums of money, securities and/or materials are transferred between owners based on the reliance of one person on the purported identity of another. Electronic systems including various cryptographic instrumentalities together with secret identity numbers or keys provide a certain amount of security; however, the amount of security is predicated upon the degree of secrecy with which one is able to secure his own special identification key. Obviously, once a person's key is learned by another, presumably an unauthorized person, the other person may falsely assume his identity for a wide variety of electronic applications.
Identity verification by means of written signatures has long been known in the art; however, most known systems have various shortcomings. Simply matching the appearance of two signatures is not satisfactory as expert forgers can usually duplicate the appearance of a person's signature as well as the person himself. The result of this is that when an expert forger is involved, even expert document examiners are frequently unable to discover that the signature is forged.
Recent developments in the field of automatic signature verification such as exemplified by U.S. Pat. No. 3,983,535 of Herbst et al and U.S. Pat. No. 4,128,829 of Herbst et al make the concept of personal identification via computer based signature analysis practical. The invention disclosed in U.S. Pat. No. 3,983,535 is based on the discovery that the accelerations of the stylus, which are proportional to the muscle forces exerted by the signer, are of predetermined consistent durations when forming particular strokes in a habitual signature. The nature of the process gives rise to various distortions in the time axis; e.g. pauses between sections of the name, skipped strokes, decorative rubrics, and the like. Thus, the signal is marked by regions of high correlation of unknown duration separated by variable regions of low correlation. Accordingly, the invention in U.S. Pat. No. 3,983,535 dealt with a method of regional correlation which registered these regions based initially on stylus contact and then shifting the regions individually to find the maximal of the correlation function weighted to penalize shifting. The results were then combined to make an overall verification decision.
The signature verification method disclosed in U.S. Pat. No. 3,983,535 was based on a single acceleration parameter of the signature dynamic, but as disclosed in U.S. Pat. No. 4,128,829, an even greater discrimination in the verification operation is possible using two orthogonally disposed (e.g. X and Y axes) acceleration components together with the pressure patterns which are produced during the writing of the signature and utilizing all three of these individual parameters in the correlation operation. The invention disclosed in U.S. Pat. No. 4,128,829 retained the concept of segmenting the sample and reference signatures, correlating individual segment pairs utilizing a series of successive shifts to obtain the maximum possible correlation, weighting the correlations, and finally combining the individual correlation statistics for all segments. An example of a pen that may be used in the Herbst et al verification system is disclosed in U.S. Pat. No. 4,142,175 of Herbst et al. This pen produces electical signals proportional to accelerations in the X and Y axes and an electrical signal proportional to the pen point pressure along the Z axis.
According to the Herbst et al procedure, reference acceleration and pressure signals are stored in memory in the electronic computer. Actually, as will be understood by those skilled in the art, digital representations of the acceleration and pressure signals are stored, and the acceleration and pressure signals produced by the pen when used to write a signature are also digitized so that all the arithemetical processing is performed digitally. In a typical system, when a customer opens an account, a signature acquisition feature on a computer terminal prompts the customer to sign his or her name several times. This produces signature data that is transmitted to the computer which selects the reference signals that are stored. Both the reference signals and the signals from the pen produced by a person whose signature is to be verified are segmented as a function of pen lifts which are detected by the pressure signal becoming zero. Pen lifts are critical to good correlation scores as they represent reproducible timing marks in the signature. The segmented acceleration and pressure signals from the pen are then compared with the corresponding reference acceleration and pressure signal segments using the correlation algorithm disclosed in U.S. Pat. No. 3,983,535 of Herbst et al. This correlation algorithm involves shifting the acceleration and pressure signal segments with respect to their corresponding reference segments in order to achieve maximum correlation. This process is carried out independently for each of the acceleration and pressure segments and results in a very high recognition ratio. However, since the correlation function is approximated by the summation of a plurality of products, the procedure can be very time consuming and resulting in delays which can be annoying to customers whose signatures are being verified. This problem can be overcome by using parallel, pipelined processors, but this is expensive.